6Conclusion

We have designed an integrated solution for ZigBee and RFID networks to achieve energy-efficient networks, which allows to selectively turn on and off the networks nodes。 Therefore, we designed a deep sleep algorithm for selection in accordance with the residual energy of nodes active nodes, thereby balancing the energy consumption of nodes in the networks。 Finally, we introduced a process to select which activate the  integrated node, not only through their remaining energy and through their spatial location。 This choice is based on the virtual plane in the networks space grid algorithm is presented and the practical application of deep sleep。 In the absence of a virtual grid configuration, we have been through the Opnet simulator performance assessment of the average residual energy, as Nmin, Es functions。 Stressed the ZigBee-RFID hybrid networks energy savings guarantee。 Configuration  of the virtual space in the case of the grid, on the contrary, we analyzed the region to effectively monitor the sensor networks and energy consumption。 In this case, the virtual space grid not only provides the same coverage,  and

can prolong the life of the networks。 This solution should be used for local stations spatial density are related。 Can create significant energy efficiency of its wireless sensor networkss。 Based on this networks has the ability to address all passive devices。

References:

1。R。 Abileah and D。 Lewis。 Monitoring high-seas fisheries with long-range passive acoustic sensors。 In Proceedings of International Conference on OCEANS’96: Prospects for the 21st Century, vol。 1, pp。 378–382, Fort Lauderdale, FL, USA, Sep。 1996。

2。I。F。 Akyildiz, W。 Su, Y。 Sankarasubramaniam, and E。 Cayirci。 A survey on sensor networkss。 IEEE Communication Magazine, 40:102–114, 2002。

3。IEEE 802。15。4 Std: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networkss (LR-WPANs)。 IEEE Computer Society Press, pp。 1–679, Oct。 2003。

4。S。 Barberis, E。 Gaiani, B。 Melis, and G。 Romano。 Performance evaluation in a large environment for the AWACS system。 In Proceedings of International Conference on Universal Personal Communications (ICUPC’98), vol。 1, pp。 721–725, Florence, Italy, Oct。 1998。

5。B。 Bougard, F。 Catthoor, D。C。 Daly, A。 Chandrakasan, and W。 Dehaene。 Energy efficiency of the IEEE 802。15。4 standard in dense wireless microsensor networkss:

Modeling and improvement perspectives。 In Proceedings of the Conference on Design, Automation and Test in Europe (DATE’05), pp。 196–201, Munich, Germany, Mar。 2005。

6。J。 Capetanakis。 Tree algorithms for packet broadcast channels。 IEEE Transactions on Information Theory, 25(5):505–515, 1979。

7。C。 Chong and S。P。 Kumar。 Sensor networkss: Evolution, opportunities and challenges。 IEEE Press, 98(8):1247–1256, Aug。 2003。

8。Inc。 Crossbow Technology。 MICAz OEM Module 2。4 GHz。 San Jose, CA, USA, 2005。 Datasheet, website: http://www。xbow。com/Products/productdetails

。aspx?sid=191

9。R。 Gallagher and D。 Bertsekas。 Data Networkss。 Prentice-Hall, Upper Saddle River, NJ, USA, 1992。

10。G。 Ferrari, F。 Cappelletti, and R。 Raheli。 A simple performance analysis of RFID networkss with binary tree collision arbitration。 International Journal on Sensor Networkss, 4(3): 61–75, 2008。

11。G。 Ferrari, P。 Medagliani, S。 Di Piazza, and M。 Martaló。 Wireless sensor networkss: Performance analysis in indoor scenarios。 EURASIP Journal of Wireless Communications and Networksing, Special Issue On Mobile Man (Mobile Multi Hop Adhoc Networkss) from theory to Reality, vol 2007, Article ID 81864, 14 pages, 2007。 DOI: 10。1155/2007/81864。